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2.
Monaldi Arch Chest Dis ; 90(3)2020 Jul 15.
Article in English | MEDLINE | ID: covidwho-649882

ABSTRACT

Italy is currently experiencing an epidemic of coronavirus disease 2019 (Covid-19). Aim of our study is to identify the best predictors of Intensive Care Unit (ICU) admission in patients with Covid-19. We examined 28 patients admitted to the Emergency Department (ED) and subsequently confirmed as cases of Covid-19. Patients received, at the admission to the ED, a diagnostic work-up including: patient history, clinical examination, an arterial blood gas analysis (whenever possible performed on room air), laboratory blood tests, including serum concentrations of interleukin-6 (IL-6), lung ultrasound examination and a computed tomography (CT) scan of the thorax. For each patient, as gas exchange index through the alveolocapillary membrane, we determined the alveolar-arterial oxygen gradient (AaDO⁠2) and the alveolar-arterial oxygen gradient augmentation (AaDO⁠2 augmentation). For each patient, as measurement of hypoxemia, we determined oxygen saturation (SpO2), partial pressure of oxygen in arterial blood (PaO⁠2), PaO⁠2 deficit and the ratio between arterial partial pressure of oxygen by blood gas analysis and fraction of inspired oxygen (P/F). Patients were assigned to ICU Group or to Non-ICU Group basing on the decision to intubate. Areas under the curve (AUC) and receiver operating characteristic (ROC) curve were used to compare the performance of each test in relation to prediction of ICU admission. Comparing patients of ICU Group (10 patients) with patients of Non-ICU Group (18 patients), we found that the first were older, they had more frequently a medical history of malignancy and they were more frequently admitted to ED for dyspnea. Patients of ICU Group had lower oxygen saturation, PaO⁠2, P/F and higher heart rate, respiratory rate, AaDO⁠2, AaDO⁠2 augmentation and lactate than patients of Non-ICU Group. ROC curves demonstrate that age, heart rate, respiratory rate, dyspnea, lactate, AaDO2, AaDO2 augmentation, white blood cell count, neutrophil count and percentage, fibrinogen, C-reactive protein, lactate dehydrogenase, glucose level, international normalized ratio (INR), blood urea and IL-6 are useful predictors of ICU admission. We identified several predictors of ICU admission in patients with Covid-19. They can act as fast tools for the early identification and timely treatment of critical cases since their arrival in the ED.


Subject(s)
Betacoronavirus , Coronavirus Infections/diagnosis , Coronavirus Infections/therapy , Critical Care , Pneumonia, Viral/diagnosis , Pneumonia, Viral/therapy , Adult , Aged , Aged, 80 and over , Blood Gas Analysis , Coronavirus Infections/complications , Emergency Service, Hospital , Female , Hospitalization , Humans , Italy , Male , Middle Aged , Pandemics , Pneumonia, Viral/complications , Predictive Value of Tests , ROC Curve , Risk Factors
3.
JAMA Netw Open ; 3(7): e2013880, 2020 07 01.
Article in English | MEDLINE | ID: covidwho-621959

ABSTRACT

Importance: During the ongoing coronavirus disease 2019 pandemic, case reports have suggested that the use of nonsteroidal anti-inflammatory drugs (NSAIDs) may lead to adverse outcomes. Objective: To study the association of NSAID use with adverse outcomes in patients hospitalized with influenza or influenza pneumonia. Design, Setting, and Participants: This cohort study used propensity score matching among 7747 individuals aged 40 years or older who were hospitalized with influenza, confirmed by polymerase chain reaction or antigen testing, between 2010 and 2018. Data were collected using Danish nationwide registers. All analyses reported were performed on May 29, 2020. Exposures: Prescription fill of an NSAID within 60 days before admission. Main Outcomes and Measures: Risk ratio (RR) and risk difference (RD) with 95% CIs for intensive care unit admission and death within 30 days of admission. Results: A total of 7747 patients (median [interquartile range] age, 71 [59-80] years, 3980 [51.4%] men) with confirmed influenza were identified. Of these, 520 (6.7%) were exposed to NSAIDs. In the unmatched cohorts, 104 of 520 patients (20.0%) who used NSAIDs and 958 of 7227 patients (13.3%) who did not use NSAIDs were admitted to the intensive care unit. For death within 30 days of admission, we observed 37 events (7.1%) among those who used NSAIDs compared with 563 events (7.8%) among those who did not. Current NSAID use was associated with intensive care unit admission (RR, 1.51; 95% CI, 1.26 to 1.81; RD, 6.7%; 95% CI, 3.2% to 10.3%), while NSAID use was not associated with death (RR, 0.91; 95% CI, 0.66 to 1.26; RD, -0.7%; 95% CI, -3.0% to 1.6%). In the matched cohorts, risks were unchanged for patients who used NSAIDs, while 83 ICU admissions (16.0%) and 36 deaths (6.9%) were observed among matched individuals who did not use NSAIDs. Matched (ie, adjusted) analyses yielded attenuated risk estimates for intensive care unit admission (RR, 1.25; 95% CI, 0.95 to 1.63; RD, 4.0%; 95% CI, -0.6% to 8.7%) and death (RR, 1.03; 95% CI, 0.66 to 1.60; RD, 0.2%; 95% CI, -2.9% to 3.3%). Associations were more pronounced among patients who used NSAIDs for a longer period (eg, for intensive care unit admission: RR, 1.90; 95% CI, 1.19 to 3.06; RD, 13.4%; 95% CI, 4.0% to 22.8%). Conclusions and Relevance: In this cohort study of adult patients hospitalized with influenza, the use of NSAIDs was not associated with 30-day intensive care unit admission or death in adjusted analyses. There was an association between long-term use of NSAIDs and intensive care unit admission.


Subject(s)
Anti-Inflammatory Agents, Non-Steroidal/pharmacology , Coronavirus Infections/drug therapy , Hospitalization , Intensive Care Units , Pneumonia, Viral/drug therapy , Adult , Aged , Aged, 80 and over , Anti-Inflammatory Agents, Non-Steroidal/adverse effects , Betacoronavirus , Cohort Studies , Coronavirus Infections/complications , Coronavirus Infections/mortality , Coronavirus Infections/virology , Denmark/epidemiology , Female , Humans , Influenza, Human , Male , Middle Aged , Odds Ratio , Pandemics , Pneumonia , Pneumonia, Viral/complications , Pneumonia, Viral/mortality , Pneumonia, Viral/virology
4.
Euro Surveill ; 25(25)2020 06.
Article in English | MEDLINE | ID: covidwho-621605

ABSTRACT

Sentinel surveillance of acute hospitalisations in response to infectious disease emergencies such as the 2009 influenza A(H1N1)pdm09 pandemic is well described, but recognition of its potential to supplement routine public health surveillance and provide scalability for emergency responses has been limited. We summarise the achievements of two national paediatric hospital surveillance networks relevant to vaccine programmes and emerging infectious diseases in Canada (Canadian Immunization Monitoring Program Active; IMPACT from 1991) and Australia (Paediatric Active Enhanced Disease Surveillance; PAEDS from 2007) and discuss opportunities and challenges in applying their model to other contexts. Both networks were established to enhance capacity to measure vaccine preventable disease burden, vaccine programme impact, and safety, with their scope occasionally being increased with emerging infectious diseases' surveillance. Their active surveillance has increased data accuracy and utility for syndromic conditions (e.g. encephalitis), pathogen-specific diseases (e.g. pertussis, rotavirus, influenza), and adverse events following immunisation (e.g. febrile seizure), enabled correlation of biological specimens with clinical context and supported responses to emerging infections (e.g. pandemic influenza, parechovirus, COVID-19). The demonstrated long-term value of continuous, rather than incident-related, operation of these networks in strengthening routine surveillance, bridging research gaps, and providing scalable public health response, supports their applicability to other countries.


Subject(s)
Hospitals, Pediatric/statistics & numerical data , Immunization Programs/standards , Patient Admission/statistics & numerical data , Population Surveillance/methods , Vaccination/adverse effects , Vaccines/administration & dosage , Australia/epidemiology , Canada/epidemiology , Child , Child, Preschool , Data Accuracy , Health Policy , Hospitalization/statistics & numerical data , Humans , National Health Programs/standards , Public Health Surveillance , Vaccination/statistics & numerical data
5.
Zhong Nan Da Xue Xue Bao Yi Xue Ban ; 45(5): 536-541, 2020 May 28.
Article in English, Chinese | MEDLINE | ID: covidwho-745337

ABSTRACT

OBJECTIVES: Since the outbreak of coronavirus disease 2019 (COVID-19), it has spread rapidly in China and many other countries. The rapid increase in the number of cases has caused widespread panic among people and has become the main public health problem in the world. Severe patients often have difficult breathing and/or hypoxemia after 1 week of onset. A few critically ill patients may not only rapidly develop into acute respiratory distress syndrome, but also may cause coagulopathy, as well as multiple organs failure (such as heart, liver and kidney) or even death. This article is to analyze the predictive role of clinical features in patients with COVID-19 for severe disease, so as to help doctor monitor the severity-related features, restrain the disease progress, and provide a reference for improvement of medical treatment. METHODS: The clinical data of 208 patients with COVID-19 who were isolated and treated in Changsha Public Health Treatment Center from January 17, 2020 to March 14, 2020 were collected. All patients were the mild and ordinary adult patients on admission, including 105 males and 103 females from 19 to 84 (median age 44) years old. According to the "Program for the diagnosis and treatment of novel coronavirus (COVID-19) infected pneumonia (Trial version 7)" issued by the General Office of National Health Committee and Office of State Administration of Traditional Chinese Medicine as the diagnostic and typing criteria. According to progression from mild to severe disease during hospitalization, the patients were divided into a mild group (n=183) and a severe transformation group (n=25). The clinical features such as age, underlying disease, blood routine, coagulation function, blood biochemistry, oxygenation index, and so on were analyzed. Among them, laboratory tests included white blood cell (WBC), lymphocytes (LYM), neutrophil (NEU), hemoglobin (Hb), platelet (PLT), prothrombin time (PT), plasma fibrinogen (Fib), activated partial prothrombin time (APTT), thrombin time (TT), D-dimer, total bilirubin (TBIL), albumin (ALB), alanine aminotransferase (ALT), aspartate aminotransferase (AST), blood urea nitrogen (BUN), serum creatinine (Cr), creatine kinase (CK), creatine kinase isoenzyme-MB (CK-MB), lactate dehydrogenase (LDH), C-reactive protein (CRP), and oxygen partial pressure in arterial blood. Partial pressure of oxygen in arterial blood/fractional concentration of inspiratory oxygen (PaO2/FiO2) was calculated. The variables with statistical significance were analyzed by logistic regression analysis. RESULTS: Patients in the severe transformation group had more combined underlying diseases than those in the mild group (P<0.05). From the perspective of disease distribution, patients in the severe transformation group had more combined hypertension (P<0.05). In the severe transformation group, PT was significantly longer, the levels of Fib, ALT, AST, CK, LDH, and CRP were significantly higher than those in the mild group (P<0.05 or P<0.001), while LYM, ALB, and PaO2/FiO2 were significantly lower than those in the mild group (P<0.05 or P<0.001). Logistic regression analysis was performed on clinical features with statistically significant differences. Combined with hypertension, LYM, PT, Fib, ALB, ALT, AST, CK, LDH, and CRP as independent variables, and having severe disease or not was the dependent variable. The results show that combined hypertension, decreased LYM, longer PT, and increased CK level were independent risk factors that affected the severity of COVID-19 (P<0.05). CONCLUSIONS: The patients with mild COVID-19 who are apt to develop severe diseases may be related to combined hypertension, decreased LYM, and longer PT, and increased CK level. For the mild patients with these clinical features, early intervention may effectively prevent the progression to severe diseases.


Subject(s)
Coronavirus Infections/diagnosis , Pneumonia, Viral/diagnosis , Adult , Aged , Aged, 80 and over , Betacoronavirus , China , Coronavirus Infections/physiopathology , Disease Progression , Female , Hospitalization , Humans , Male , Middle Aged , Pandemics , Pneumonia, Viral/physiopathology , Retrospective Studies , Young Adult
6.
Eur Respir J ; 56(2)2020 08.
Article in English | MEDLINE | ID: covidwho-744960

ABSTRACT

BACKGROUND: The outbreak of coronavirus disease 2019 (COVID-19) has globally strained medical resources and caused significant mortality. OBJECTIVE: To develop and validate a machine-learning model based on clinical features for severity risk assessment and triage for COVID-19 patients at hospital admission. METHOD: 725 patients were used to train and validate the model. This included a retrospective cohort from Wuhan, China of 299 hospitalised COVID-19 patients from 23 December 2019 to 13 February 2020, and five cohorts with 426 patients from eight centres in China, Italy and Belgium from 20 February 2020 to 21 March 2020. The main outcome was the onset of severe or critical illness during hospitalisation. Model performances were quantified using the area under the receiver operating characteristic curve (AUC) and metrics derived from the confusion matrix. RESULTS: In the retrospective cohort, the median age was 50 years and 137 (45.8%) were male. In the five test cohorts, the median age was 62 years and 236 (55.4%) were male. The model was prospectively validated on five cohorts yielding AUCs ranging from 0.84 to 0.93, with accuracies ranging from 74.4% to 87.5%, sensitivities ranging from 75.0% to 96.9%, and specificities ranging from 55.0% to 88.0%, most of which performed better than the pneumonia severity index. The cut-off values of the low-, medium- and high-risk probabilities were 0.21 and 0.80. The online calculators can be found at www.covid19risk.ai. CONCLUSION: The machine-learning model, nomogram and online calculator might be useful to access the onset of severe and critical illness among COVID-19 patients and triage at hospital admission.


Subject(s)
Coronavirus Infections/diagnosis , Hospital Mortality/trends , Machine Learning , Pneumonia, Viral/diagnosis , Triage/methods , Adult , Age Factors , Aged , Area Under Curve , Belgium , China , Clinical Laboratory Techniques , Cohort Studies , Coronavirus Infections/epidemiology , Decision Support Systems, Clinical , Female , Hospitalization/statistics & numerical data , Humans , Internationality , Italy , Male , Middle Aged , Pandemics/statistics & numerical data , Pneumonia, Viral/epidemiology , Predictive Value of Tests , ROC Curve , Reproducibility of Results , Retrospective Studies , Risk Assessment , Severity of Illness Index , Sex Factors , Survival Analysis
7.
Eur Respir J ; 56(2)2020 08.
Article in English | MEDLINE | ID: covidwho-744959

ABSTRACT

BACKGROUND: Timely diagnosis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is a prerequisite for treatment and prevention. The serology characteristics and complement diagnosis value of the antibody test to RNA test need to be demonstrated. METHOD: Serial sera of 80 patients with PCR-confirmed coronavirus disease 2019 (COVID-19) were collected at the First Affiliated Hospital of Zhejiang University, Hangzhou, China. Total antibody (Ab), IgM and IgG antibodies against SARS-CoV-2 were detected, and the antibody dynamics during the infection were described. RESULTS: The seroconversion rates for Ab, IgM and IgG were 98.8%, 93.8% and 93.8%, respectively. The first detectible serology marker was Ab, followed by IgM and IgG, with a median seroconversion time of 15, 18 and 20 days post exposure (d.p.e.) or 9, 10 and 12 days post onset (d.p.o.), respectively. The antibody levels increased rapidly beginning at 6 d.p.o. and were accompanied by a decline in viral load. For patients in the early stage of illness (0-7 d.p.o), Ab showed the highest sensitivity (64.1%) compared with IgM and IgG (33.3% for both; p<0.001). The sensitivities of Ab, IgM and IgG increased to 100%, 96.7% and 93.3%, respectively, 2 weeks later. When the same antibody type was detected, no significant difference was observed between enzyme-linked immunosorbent assays and other forms of immunoassays. CONCLUSIONS: A typical acute antibody response is induced during SARS-CoV-2 infection. Serology testing provides an important complement to RNA testing in the later stages of illness for pathogenic-specific diagnosis and helpful information to evaluate the adapted immunity status of patients.


Subject(s)
Betacoronavirus , Clinical Laboratory Techniques , Coronavirus Infections/blood , Coronavirus Infections/diagnosis , Pneumonia, Viral/blood , Pneumonia, Viral/diagnosis , Adult , Aged , China , Coronavirus Infections/complications , Female , Hospitalization , Humans , Infectious Disease Incubation Period , Male , Middle Aged , Pandemics , Pneumonia, Viral/complications , Sensitivity and Specificity , Seroconversion , Symptom Assessment , Time Factors , Viral Load
8.
In Vivo ; 34(5): 3033-3038, 2020.
Article in English | MEDLINE | ID: covidwho-740634

ABSTRACT

BACKGROUND/AIM: SARS-CoV-2 pandemic imposed extraordinary restriction measures and a complete reorganization of the Health System. The aim of the study was to evaluate the impact of COVID-19 on emergency surgical department accesses. PATIENTS AND METHODS: Patients admitted to surgical emergency departments was retrospectively recorded during the Lockdown (March 11, 2020-May 3, 2020) and compared with the same number of days in 2019 and immediately before Lockdown (January 16, 2020-March 10, 2020). Diagnoses, priority levels, modes of patient's transportation, waiting times and outcomes were analysed. RESULTS: During the lockdown phase, we ob-served a reduction in the access to emergency surgical departments of 84.45% and 79.78%, com-pared with the Pre-Lockdown2019 and Pre-Lockdown2020 groups, respectively. Patient's transportation, hospitalization and patients discharge with indications to an outpatient visit, waiting and total times exhibited a significant difference during the lockdown (p<0.005). CONCLUSION: We observed a reduction of surgical emergency accesses during the lockdown. Implementing the use of the regional systems and preventing overcrowding of emergency departments could be beneficial for reducing waiting times and improving the quality of treatments for patients.


Subject(s)
Coronavirus Infections/epidemiology , Emergency Service, Hospital/statistics & numerical data , Pandemics , Pneumonia, Viral/epidemiology , Surgery Department, Hospital/statistics & numerical data , Betacoronavirus/pathogenicity , Female , Health Systems Plans , Hospitalization , Humans , Italy/epidemiology , Male , Retrospective Studies
9.
In Vivo ; 34(5): 3029-3032, 2020.
Article in English | MEDLINE | ID: covidwho-740633

ABSTRACT

BACKGROUND/AIM: Reports indicate that coronaviridae may inhibit insulin secretion. In this report we aimed to describe the course of glycemia in critically ill patients with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection. PATIENTS AND METHODS: We studied 36 SARS-CoV-2 patients (with no history of diabetes) in one intensive care unit (ICU). All the patients were admitted for hypoxemic respiratory failure; all but four required mechanical ventilation. The mean (±SD) age of the patients was 64.7 (9.7) years; 27 were men; the mean (±SD) duration of ICU stay was 12.9 (8.3 days). RESULTS: Twenty of 36 patients presented with hyperglycemia; brief intravenous infusions of short-acting insulin were administered in six patients. As of May 29 2020, 11 patients had died (seven with hyperglycemia). In 17 patients the Hyperglycemia Index [HGI; defined as the area under the curve of (hyper)glycemia level*time (h) divided by the total time in the ICU] was <16.21 mg/dl (0.90 mmol/l), whereas in three patients the HGI was ≥16.21 mg/dl (0.90 mol/l) and <32.25 mg/dl (1.79 mmol/l). CONCLUSION: In our series of ICU patients with SARS-CoV-2 infection, and no history of diabetes, a substantial number of patients had hyperglycemia, to a higher degree than would be expected by the stress of critical illness, lending credence to reports that speculated a tentative association between SARS-CoV-2 and hyperglycemia. This finding is important, since hyperglycemia can lead to further infectious complications.


Subject(s)
Coronavirus Infections/therapy , Diabetes Mellitus/therapy , Hyperglycemia/therapy , Insulin/metabolism , Pneumonia, Viral/therapy , Betacoronavirus/pathogenicity , Blood Glucose/metabolism , Coronavirus Infections/complications , Coronavirus Infections/virology , Diabetes Mellitus/genetics , Diabetes Mellitus/virology , Female , Hospitalization , Humans , Hyperglycemia/complications , Hyperglycemia/virology , Intensive Care Units , Male , Middle Aged , Pandemics , Pneumonia, Viral/complications , Pneumonia, Viral/virology , Respiration, Artificial , Respiratory Insufficiency/physiopathology , Respiratory Insufficiency/therapy , Severe Acute Respiratory Syndrome/complications , Severe Acute Respiratory Syndrome/therapy , Severe Acute Respiratory Syndrome/virology
11.
BMC Infect Dis ; 20(1): 644, 2020 Sep 01.
Article in English | MEDLINE | ID: covidwho-740367

ABSTRACT

BACKGROUND: To explore the clinical features and CT findings of clinically cured coronavirus disease 2019 (COVID-19) patients with viral RNA positive anal swab results after discharge. METHODS: Forty-two patients with COVID-19 who were admitted to Yongzhou Central Hospital, Hunan, China, between January 20, 2020, and March 2, 2020, were tested for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) using anal swab viral RT-PCR. In this report, we present the clinical characteristics and chest CT features of six patients with positive anal swab results and compare the clinical, laboratory, and CT findings between the positive and negative groups. RESULTS: The anal swab positivity rate for SARS-CoV-2 RNA in discharged patients was 14.3% (6/42). All six patients were male. In the positive group, 40% of the patients (2/5) had a positive stool occult blood test (OBT), but none had diarrhea. The median duration of fever and major symptoms (except fever) in the positive patients was shorter than that of the negative patients (1 day vs. 6 days, 4.5 days vs. 10.5 days, respectively). The incidence of asymptomatic cases in the positive group (33.3%) was also higher than that of the negative group (5.6%). There were no significant differences in the CT manifestation or evolution of the pulmonary lesions between the two groups. CONCLUSION: In our case series, patients with viral RNA positive anal swabs did not exhibit gastrointestinal symptoms, and their main symptoms disappeared early. They had similar CT features to the negative patients, which may be easier to be ignored. A positive OBT may indicate gastrointestinal damage caused by SARS-CoV-2 infection.


Subject(s)
Betacoronavirus/isolation & purification , Coronavirus Infections/diagnostic imaging , Patient Discharge/statistics & numerical data , Pneumonia, Viral/diagnostic imaging , RNA, Viral/analysis , Severe Acute Respiratory Syndrome/diagnostic imaging , Adolescent , Adult , Aged , Anal Canal/virology , Betacoronavirus/genetics , Child , Child, Preschool , China/epidemiology , Coronavirus Infections/epidemiology , Coronavirus Infections/virology , Fever , Hospitalization , Hospitals , Humans , Male , Middle Aged , Pandemics , Pneumonia, Viral/epidemiology , Pneumonia, Viral/virology , Reverse Transcriptase Polymerase Chain Reaction , Severe Acute Respiratory Syndrome/epidemiology , Severe Acute Respiratory Syndrome/virology , Tomography, X-Ray Computed , Young Adult
12.
Medicine (Baltimore) ; 99(35): e21700, 2020 Aug 28.
Article in English | MEDLINE | ID: covidwho-740200

ABSTRACT

The coronavirus disease 2019 (COVID-19) outbreak has become a global health threat and will likely be one of the greatest global challenges in the near future. The battle between clinicians and the COVID-19 outbreak may be a "protracted war."The objective of this study was to investigate the risk factors for in-hospital mortality in patients with COVID-19, so as to provide a reference for the early diagnosis and treatment.This study retrospectively enrolled 118 patients diagnosed with COVID-19, who were admitted to Eastern District of Renmin Hospital of Wuhan University from February 04, 2020 to March 04, 2020. The demographics and laboratory data were collected and compared between survivors and nonsurvivors. The risk factors of in-hospital mortality were explored by univariable and multivariable logistic regression to construct a clinical prediction model, the prediction efficiency of which was verified by receiver-operating characteristic (ROC) curve.A total of 118 patients (49 males and 69 females) were included in this study; the results revealed that the following factors associated with in-hospital mortality: older age (odds ratio [OR] 1.175, 95% confidence interval [CI] 1.073-1.287, P = .001), neutrophil count greater than 6.3 × 10 cells/L (OR 7.174, (95% CI 2.295-22.432, P = .001), lymphocytopenia (OR 0.069, 95% CI 0.007-0.722, P = .026), prothrombin time >13 seconds (OR 11.869, 95% CI 1.433-98.278, P = .022), D-dimer >1 mg/L (OR 22.811, 95% CI 2.224-233.910, P = .008) and procalcitonin (PCT) >0.1 ng/mL (OR 23.022, 95% CI 3.108-170.532, P = .002). The area under the ROC curve (AUC) of the above indicators for predicting in-hospital mortality were 0.808 (95% CI 0.715-0.901), 0.809 (95% CI 0.710-0.907), 0.811 (95% CI 0.724-0.898), 0.745 (95% CI 0.643-0.847), 0.872 (95% CI 0.804-0.940), 0.881 (95% CI 0.809-0.953), respectively. The AUC of combined diagnosis of these aforementioned factors were 0.992 (95% CI 0.981-1.000).In conclusion, older age, increased neutrophil count, prothrombin time, D-dimer, PCT, and decreased lymphocyte count at admission were risk factors associated with in-hospital mortality of COVID-19. The prediction model combined of these factors could improve the early identification of mortality risk in COVID-19 patients.


Subject(s)
Coronavirus Infections , Fibrin Fibrinogen Degradation Products/analysis , Leukocyte Count , Pandemics , Pneumonia, Viral , Procalcitonin/analysis , Prothrombin Time , Adult , Aged , Betacoronavirus , China/epidemiology , Coronavirus Infections/blood , Coronavirus Infections/immunology , Coronavirus Infections/mortality , Female , Hospital Mortality , Hospitalization/statistics & numerical data , Humans , Leukocyte Count/methods , Leukocyte Count/statistics & numerical data , Male , Pneumonia, Viral/blood , Pneumonia, Viral/immunology , Pneumonia, Viral/mortality , Predictive Value of Tests , Prognosis , Prothrombin Time/methods , Prothrombin Time/statistics & numerical data , Retrospective Studies , Risk Assessment/methods , Risk Factors
13.
BMJ Open ; 10(8): e039455, 2020 08 30.
Article in English | MEDLINE | ID: covidwho-737538

ABSTRACT

INTRODUCTION: The outbreak of the SARS-CoV-2 virus causing COVID-19, declared a global pandemic by the WHO, is a novel infection with a high rate of morbidity and mortality. In South Africa, 55 421 cases have been confirmed as of 10 June 2020, with most cases in the Western Cape Province. Coronavirus leaves us in a position of uncertainty regarding the best clinical approach to successfully manage the expected high number of severely ill patients with COVID-19. This presents a unique opportunity to gather data to inform best practices in clinical approach and public health interventions to control COVID-19 locally. Furthermore, this pandemic challenges our resolve due to the high burden of HIV and tuberculosis (TB) in our country as data are scarce. This study endeavours to determine the clinical presentation, severity and prognosis of patients with COVID-19 admitted to our hospital. METHODS AND ANALYSIS: The study will use multiple approaches taking into account the evolving nature of the COVID-19 pandemic. Prospective observational design to describe specific patterns of risk predictors of poor outcomes among patients with severe COVID-19 admitted to Tygerberg Hospital. Data will be collected from medical records of patients with severe COVID-19 admitted at Tygerberg Hospital. Using the Cox proportional hazards model, we will investigate the association between the survival time of patients with COVID-19 in relation to one or more of the predictor variables including HIV and TB. ETHICS AND DISSEMINATION: The research team obtained ethical approval from the Health Research Ethics Committee of the Faculty of Medicine and Health Sciences, Stellenbosch University and Research Committee of the Tygerberg Hospital. All procedures for the ethical conduct of scientific investigation will be adhered to by the research team. The findings will be disseminated in clinical seminars, scientific forums and conferences targeting clinical care providers and policy-makers.


Subject(s)
Coronavirus Infections , Hospitalization , Hospitals , Pandemics , Pneumonia, Viral , Betacoronavirus , Coronavirus Infections/epidemiology , Coronavirus Infections/therapy , Coronavirus Infections/virology , Disease Outbreaks , Female , HIV Infections/complications , Humans , Male , Medical Records , Pneumonia, Viral/epidemiology , Pneumonia, Viral/therapy , Pneumonia, Viral/virology , Proportional Hazards Models , Prospective Studies , Public Health , Research Design , South Africa/epidemiology , Survivors , Tuberculosis/complications
14.
J Prim Care Community Health ; 11: 2150132720954687, 2020.
Article in English | MEDLINE | ID: covidwho-737527

ABSTRACT

BACKGROUND: COVID-19 is a highly infectious disease which usually presents with respiratory symptoms. This virus is disseminated through respiratory droplets, and, therefore, individuals residing in close quarters are at a higher risk for the acquisition of infection. The prison population is at a significantly increased risk for infection. METHODS: Prisoners from the Montford Correctional facility in Lubbock, Texas, hospitalized in the medical intensive care unit at University Medical Center between March 1, 2020 and May 15, 2020 were compared to community-based patients hospitalized in the same medical intensive care unit. Clinical information, laboratory results, radiographic results, management requirements, and outcomes were compared. RESULTS: A total of 15 community-based patients with a mean age of 67.4 ± 15.5 years were compared to 5 prisoners with a mean age of 56.0 ± 9.0 years. All prisoners were men; 10 community-based patients were men. Prisoners presented with fever, dyspnea, and GI symptoms. The mean number of comorbidities in prisoners was 2.4 compared to 1.8 in community-based patients. Prisoners had significantly lower heart rates and respiratory rates at presentation than community-based patients. The mean length of stay in prisoners was 12.6 ± 8.9 days; the mean length of stay in community-based patients was 8.6 ± 6.5. The case fatality rate was 60% in both groups. CONCLUSIONS: Prisoners were younger than community-based patients but required longer lengths of stay and had the same mortality rate. This study provides a basis for comparisons with future studies which could involve new treatment options currently under study.


Subject(s)
Coronavirus Infections/therapy , Critical Care/statistics & numerical data , Pandemics , Patients/statistics & numerical data , Pneumonia, Viral/therapy , Prisoners/statistics & numerical data , Academic Medical Centers , Age Distribution , Aged , Aged, 80 and over , Comorbidity , Coronavirus Infections/epidemiology , Coronavirus Infections/mortality , Female , Hospitalization , Humans , Intensive Care Units , Length of Stay/statistics & numerical data , Male , Middle Aged , Pneumonia, Viral/epidemiology , Pneumonia, Viral/mortality , Retrospective Studies , Texas/epidemiology , Treatment Outcome
15.
Nat Commun ; 11(1): 4264, 2020 08 26.
Article in English | MEDLINE | ID: covidwho-733526

ABSTRACT

The pressing need to restart socioeconomic activities locked-down to control the spread of SARS-CoV-2 in Italy must be coupled with effective methodologies to selectively relax containment measures. Here we employ a spatially explicit model, properly attentive to the role of inapparent infections, capable of: estimating the expected unfolding of the outbreak under continuous lockdown (baseline trajectory); assessing deviations from the baseline, should lockdown relaxations result in increased disease transmission; calculating the isolation effort required to prevent a resurgence of the outbreak. A 40% increase in effective transmission would yield a rebound of infections. A control effort capable of isolating daily  ~5.5% of the exposed and highly infectious individuals proves necessary to maintain the epidemic curve onto the decreasing baseline trajectory. We finally provide an ex-post assessment based on the epidemiological data that became available after the initial analysis and estimate the actual disease transmission that occurred after weakening the lockdown.


Subject(s)
Communicable Disease Control/standards , Coronavirus Infections/epidemiology , Coronavirus Infections/prevention & control , Pandemics/prevention & control , Pneumonia, Viral/epidemiology , Pneumonia, Viral/prevention & control , Basic Reproduction Number , Betacoronavirus , Communicable Disease Control/trends , Coronavirus Infections/transmission , Forecasting , Geography , Hospitalization/statistics & numerical data , Hospitalization/trends , Humans , Italy/epidemiology , Models, Theoretical , Pneumonia, Viral/transmission , Social Isolation
16.
Medicine (Baltimore) ; 99(34): e21824, 2020 Aug 21.
Article in English | MEDLINE | ID: covidwho-733318

ABSTRACT

In December 2019, a cluster of coronavirus Disease 2019 (COVID-19) occurred in Wuhan, Hubei Province, China. The present study was conducted to report the clinical characteristics of 201 COVID-19 patients in Changsha, China, a city outside of Wuhan. All of the patients with confirmed COVID-19 were admitted to the First Hospital of Changsha City, the designated hospital for COVID-19 assigned by the Changsha City Government. The clinical and epidemiological characteristics, data of laboratory, radiological picture, treatment, and outcomes records of 201 COVID-19 patients were collected using electronic medical records. This study population consisted of 201 hospitalized patients with laboratory-confirmed COVID-19 in Changsha by April 28, 2020. The median age of the patients was 45 years (IQR 34-59). About half (50.7%) of the patients were male, and most of the infected patients were staff (96 [47.8%]). Concerning the epidemiologic history, the number of patients linked to Wuhan was 92 (45.8%). The most common symptoms were fever (125 [62.2%]), dry cough (118 [58.7%]), fatigue (65 [32.3%]), and pharyngalgia (31 [15.4%]). One hundred and forty-four (71.6%) enrolled patients showed bilateral pneumonia. Fifty-four (26.9%) patients showed unilateral involvement, and three (1.5%) patients showed no abnormal signs or symptoms. The laboratory findings differed significantly between the Intensive Care Unit (ICU) and non-ICU groups. Compared with non-ICU patients, ICU patients had depressed white blood cell (WBC), neutrocytes, lymphocytes, and prolonged prothrombin time (PT). Moreover, higher plasma levels of erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), procalcitonin (PCT), alanine aminotransferase (ALA), aspartate aminotransferase (AST), creatine kinase (CK), creatine kinase-MB (CK-MB), creatinine (CREA), and lactate dehydrogenase (LDH) were detected in the ICU group. In this single-center study of 201 COVID-19 patients in Changsha, China, 22.4% of patients were admitted to ICU. Based on our findings, we propose that the risk of cellular immune deficiency, hepatic injury, and kidney injury should be monitored. Previous reports focused on the clinical features of patients from Wuhan, China. With the global epidemic of COVID-19, we should pay more attention to the clinical and epidemiological characteristics of patients outside of Wuhan.


Subject(s)
Coronavirus Infections/epidemiology , Coronavirus Infections/physiopathology , Pneumonia, Viral/epidemiology , Pneumonia, Viral/physiopathology , Adult , Betacoronavirus , China/epidemiology , Coronavirus Infections/complications , Cough/epidemiology , Female , Fever/epidemiology , Hospitalization/statistics & numerical data , Humans , Intensive Care Units/statistics & numerical data , Male , Middle Aged , Pandemics , Pneumonia, Viral/complications , Real-Time Polymerase Chain Reaction
17.
PLoS One ; 15(8): e0238281, 2020.
Article in English | MEDLINE | ID: covidwho-732997

ABSTRACT

This is a population-based prospective cohort study on archive data describing the age- and sex-specific prevalence of COVID-19 and its prognostic factors. All 2653 symptomatic patients tested positive for SARS-CoV-2 from February 27 to April 2, 2020 in the Reggio Emilia province, Italy, were included. COVID-19 cumulative incidence, hospitalization and death rates, and adjusted hazard ratios (HR) with 95% confidence interval (95% CI) were calculated according to sociodemographic and clinical characteristics. Females had higher prevalence of infection than males below age 50 (2.61 vs. 1.84 ‰), but lower in older ages (16.49 vs. 20.86 ‰ over age 80). Case fatality rate reached 20.7% in cases with more than 4 weeks follow up. After adjusting for age and comorbidities, men had a higher risk of hospitalization (HR 1.4 95% CI 1.2 to 1.6) and of death (HR 1.6, 95% CI 1.2 to 2.1). Patients over age 80 compared to age < 50 had HR 7.1 (95% CI 5.4 to 9.3) and HR 27.8 (95% CI 12.5 to 61.7) for hospitalization and death, respectively. Immigrants had a higher risk of hospitalization (HR 1.3, 95% CI 0.99 to 1.81) than Italians and a similar risk of death. Risk of hospitalization and of death were higher in patients with heart failure, arrhythmia, dementia, coronary heart disease, diabetes, and hypertension, while COPD increased the risk of hospitalization (HR 1.9, 95% CI 1.4 to 2.5) but not of death (HR 1.1, 95% CI 0.7 to 1.7). Previous use of ACE inhibitors had no effect on risk of death (HR 0.97, 95% CI 0.69 to 1.34). Identified susceptible populations and fragile patients should be considered when setting priorities in public health planning and clinical decision making.


Subject(s)
Coronavirus Infections/epidemiology , Hospitalization/statistics & numerical data , Pneumonia, Viral/epidemiology , Age Distribution , Aged , Aged, 80 and over , Betacoronavirus , Comorbidity , Coronavirus Infections/mortality , Emigrants and Immigrants/statistics & numerical data , Female , Humans , Incidence , Italy/epidemiology , Male , Middle Aged , Pandemics , Pneumonia, Viral/mortality , Proportional Hazards Models , Prospective Studies , Risk Factors , Sex Distribution
20.
Theranostics ; 10(21): 9663-9673, 2020.
Article in English | MEDLINE | ID: covidwho-732688

ABSTRACT

Introduction: To explore the involvement of the cardiovascular system in coronavirus disease 2019 (COVID-19), we investigated whether myocardial injury occurred in COVID-19 patients and assessed the performance of serum high-sensitivity cardiac Troponin I (hs-cTnI) levels in predicting disease severity and 30-day in-hospital fatality. Methods: We included 244 COVID-19 patients, who were admitted to Renmin Hospital of Wuhan University with no preexisting cardiovascular disease or renal dysfunction. We analyzed the data including patients' clinical characteristics, cardiac biomarkers, severity of medical conditions, and 30-day in-hospital fatality. We performed multivariable Cox regressions and the receiver operating characteristic analysis to assess the association of cardiac biomarkers on admission with disease severity and prognosis. Results: In this retrospective observational study, 11% of COVID-19 patients had increased hs-cTnI levels (>40 ng/L) on admission. Of note, serum hs-cTnI levels were positively associated with the severity of medical conditions (median [interquartile range (IQR)]: 6.00 [6.00-6.00] ng/L in 91 patients with moderate conditions, 6.00 [6.00-18.00] ng/L in 107 patients with severe conditions, and 11.00 [6.00-56.75] ng/L in 46 patients with critical conditions, P for trend=0.001). Moreover, compared with those with normal cTnI levels, patients with increased hs-cTnI levels had higher in-hospital fatality (adjusted hazard ratio [95% CI]: 4.79 [1.46-15.69]). The receiver-operating characteristic curve analysis suggested that the inclusion of hs-cTnI levels into a panel of empirical prognostic factors substantially improved the prediction performance for severe or critical conditions (area under the curve (AUC): 0.71 (95% CI: 0.65-0.78) vs. 0.65 (0.58-0.72), P=0.01), as well as for 30-day fatality (AUC: 0.91 (0.85-0.96) vs. 0.77 (0.62-0.91), P=0.04). A cutoff value of 20 ng/L of hs-cTnI level led to the best prediction to 30-day fatality. Conclusions: In COVID-19 patients with no preexisting cardiovascular disease, 11% had increased hs-cTnI levels. Besides empirical prognostic factors, serum hs-cTnI levels upon admission provided independent prediction to both the severity of the medical condition and 30-day in-hospital fatality. These findings may shed important light on the clinical management of COVID-19.


Subject(s)
Cardiomyopathies/etiology , Coronavirus Infections/complications , Pneumonia, Viral/complications , Troponin I/blood , Aged , Cardiomyopathies/blood , China , Cohort Studies , Coronavirus Infections/blood , Coronavirus Infections/mortality , Female , Hospitalization , Humans , Male , Middle Aged , Pandemics , Pneumonia, Viral/blood , Pneumonia, Viral/mortality , Predictive Value of Tests , Prognosis , Retrospective Studies
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